Big Data Analytics in Healthcare Using Spreadsheets

Iyengar, Samaya Pillai; Acharya, Haridas; Kadam, Manik

doi:10.1007/978-3-030-31672-3_9

Cited by 4 publications

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“… No Citation Technique Description 1 56 Network foresight approach To provide an easy and timely data-access interface this research work used networked foresight approach for the prediction of accurate medicine using current and past clinical historical information. This approach provides an easier interface for the patients and doctors to communicate and exchange information regarding their health status 2 8 – 11 , 19 , 57 , 63 , 73 , 78 , 82 , 86 , 92 , 95 , 97 , 111 – 113 , 116 , 120 , 123 – 126 , 128 , 129 , 131 – 133 , 135 , 137 , 139 – 141 , 144 – 147 , 149 – 154 , 156 , 157 Big data analytics for timely data-access purposes These survey papers presents applications of big data analytics in term of facilities like presenting an easier and timely-access mechanism for both patients and practitioners 3 70 , 197 Pig Latin Script programming tool Pig Latin Script is applied to analyse the healthcare datasets against different queries, to enhance health facilities in ...…”

Section: Resultsmentioning

confidence: 99%

“…To provide an easy and timely data-access interface this research work used networked foresight approach for the prediction of accurate medicine using current and past clinical historical information. This approach provides an easier interface for the patients and doctors to communicate and exchange information regarding their health status 2 [8][9][10][11]19,57,63,73,78,82,86,92,95,97,[111][112][113]116,120,[123][124][125][126]128,129,[131][132][133]135,137,[139][140][141][144][145][146][147][149][150][151][152][153][154]156,157 Big data analytics for timely data-access purposes…”

Section: Network Foresight Approachmentioning

confidence: 99%

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Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Khan

Nazir

2022

Sci Rep

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Big data has revolutionized the world by providing tremendous opportunities for a variety of applications. It contains a gigantic amount of data, especially a plethora of data types that has been significantly useful in diverse research domains. In healthcare domain, the researchers use computational devices to extract enriched relevant information from this data and develop smart applications to solve real-life problems in a timely fashion. Electronic health (eHealth) and mobile health (mHealth) facilities alongwith the availability of new computational models have enabled the doctors and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. Digital transformation of healthcare systems by using of information system, medical technology, handheld and smart wearable devices has posed many challenges to researchers and caretakers in the form of storage, minimizing treatment cost, and processing time (to extract enriched information, and minimize error rates to make optimum decisions). In this research work, the existing literature is analysed and assessed, to identify gaps that result in affecting the overall performance of the available healthcare applications. Also, it aims to suggest enhanced solutions to address these gaps. In this comprehensive systematic research work, the existing literature reported during 2011 to 2021, is thoroughly analysed for identifying the efforts made to facilitate the doctors and practitioners for diagnosing diseases using healthcare big data analytics. A set of rresearch questions are formulated to analyse the relevant articles for identifying the key features and optimum management solutions, and laterally use these analyses to achieve effective outcomes. The results of this systematic mapping conclude that despite of hard efforts made in the domains of healthcare big data analytics, the newer hybrid machine learning based systems and cloud computing-based models should be adapted to reduce treatment cost, simulation time and achieve improved quality of care. This systematic mapping will also result in enhancing the capabilities of doctors, practitioners, researchers, and policymakers to use this study as evidence for future research.

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Section: Resultsmentioning

confidence: 99%

Section: Network Foresight Approachmentioning

confidence: 99%

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Khan

Nazir

2022

Sci Rep

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A supervised biosensor-based non-variant structuring approach for analyzing infectious disease data

et al. 2022

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A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming

Nazir

Khan

et al. 2020

IEEE Access

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Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015-2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly. INDEX TERMS Healthcare, big data, big data management, big data analytics.

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Big Data Analytics in Healthcare Using Spreadsheets

Cited by 4 publications

References 0 publications

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

A supervised biosensor-based non-variant structuring approach for analyzing infectious disease data

A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming

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